Gradual Covering Location Problems And Approach Based On Service Quality

In different industries and fields’location problems, consumers are usually the key factor we should consider. The aim of facility location is to increase enterprise profits by provide better service and attract more consumers, especially in the service industries and public utilities. The level of perception of public satisfaction and quality of service often become key factors for enterprise survival in a competitive environment. Therefore, some soft targets such as the level of quality of service, service efficiency, and public satisfaction become unavoidable factor in location decisions; sometimes we should consider them in priority. In this paper, considering the strategic decisions, the above factors are analyzed. This paper studies facility location problems under different situations. Models are built on different background, lagrangian relaxation algorithm and many other heuristic algorithms are proposed.Firstly, this paper gives the background and significance of facility location problems based on service quality. Considering the disadvantages of the current study, we present innovations of this dissertation. Then gives the main contents of gradual covering facility location problems, and the current research status are reviewed.Secondly, the gradual coverage location problems based on service quality are studied. Considering customer satisfaction and service quality, we modify the existing current models more applicable in practice under the description of the gradual covering function. Taking into account different service standards and fairness, a new model based on the level of service quality are proposed. And the levels of quality are determined by the decision-makers. This will give the decision-makers more choices.We also solve this model with Lagrange heuristic algorithm. Computational results illustrated the effectiveness of the solution procedures are presented.Thirdly, Multi-object gradually covering location problems based on service quality are investigated. Most existing location models have clear and exact quantitative description of covering indicators when considering demand coverings. But it doesn’t always work in practical application. Secondly, many models can’t fit the scheme well only by using single object function. Moreover, the size and type of facilities have an important impact on location when considering other factors such as capacity constraints or cost. We should consider the combination of qualitative and quantitative factors in reality. Hence, multi-object optimization based on fuzzy sets will be better able to reflect the real-world applications. Decision-makers will have more choices when facing existing schemes. We expand existing covering models by multi-object facility location optimization. Heuristic algorithms are presented and the results were analyzed.Fourthly, the joint coverage model based on the fairness and service efficiency are studied. Some literatures only consider maximal covering on the condition of fixed costs in spite of the fairness of all demand points. Some others only consider all demand points should be covered in spite of efficiency. Both of them have obviously shortcomings.In this paper, we consider more realistic models-the combination of joint covering and gradual covering model. Service quality of unit cost is the highest when all demand service level reaches a given minimum value on the basis of quality of service. Sensitivity analyses are proposed considering deferent indicators that maybe influence service qualities.Finally, a comprehensive summary of the paper and future research are discussed.